330 results about "Noise power" patented technology

The invention relates to a channel estimation method based on frequency domain deviation compensation and dynamic DCT denoising, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a wireless channel model and an OFDM system model; estimating the frequency offset in the received signal by using the phase rotation characteristic of the pilot signal; calculating a preliminary channel frequency domain response # imgabs2 # at a pilot frequency position through a least square criterion based on the compensation signal # imgabs1 #; obtaining a receiving pilot frequency signal # imgabs4 # according to the sending pilot frequency Xp and the roughly estimated channel frequency response # imgabs3 #; estimating a current signal-to-noise ratio SNRest based on the pilot frequency signal # imgabs5 # and a noise power ratio; and establishing an adaptive DCT denoising strategy based on a signal-to-noise ratio threshold, and selecting different denoising strategies according to different signal-to-noise ratios to perform denoising processing on # imgabs6 # to obtain final channel estimation # imgabs7 #. The adaptive denoising strategy design of the invention effectively balances the relationship between noise suppression and channel structure fidelity, and improves the precision and stability of overall channel estimation.

The invention discloses a power supply communication method and device based on power line carrier communication, and relates to the technical field of power supply communication. Problems of signal attenuation, insufficient anti-interference capability, insufficient stability of power supply communication, insufficient intelligent path switching capability and the like exist in the prior art. According to the method, high-sampling-rate PSD analysis, STFT and LSTM are adopted to predict noise power time sequence data, and a noise-load rate coupling model is established; secondly, based on a transmission line theory, researching channel time-varying characteristics, calculating signal reflection and multipath effects, and calculating channel coherence time through a sliding window; for signal attenuation, low, medium and high frequency band models are respectively established, path attenuation is calculated, and channel capacity is optimized; and finally, through real-time stability analysis, short-term and long-term SNR stability is calculated, and path selection is optimized in combination with a load rate, so that communication quality is ensured. And through integration of channel modeling, time-varying analysis and path optimization, the reliability and stability of power line carrier communication are improved.

The invention discloses a sparse Bayesian direction of arrival estimation method based on subspace compression and dictionary optimization, and belongs to the field of array signal processing. According to the method, the data dimension is reduced through the subspace compression technology, and the noise immunity is improved; signal power and noise power are automatically estimated in combination with a sparse Bayesian model, and dependence on information source number information is avoided; the calculation efficiency and the numerical stability are improved through a support set adaptive pruning strategy; and finally, a dictionary fine tuning mechanism is introduced, direction continuous optimization is realized on the basis of an original discrete grid, an off-grid error is eliminated, and direction-of-arrival estimation with sub-resolution precision is realized. The method is a novel method combining subspace compression, sparse Bayesian inference, adaptive pruning and angle optimization, can give consideration to estimation precision, calculation efficiency and application robustness, and is especially suitable for direction estimation under the complex actual conditions of low signal-to-noise ratio, few snapshots, unknown signal source number and the like.

The invention relates to the technical field of satellite transmission service or radio transmission service of a space station or an airborne station, in particular to a narrow-band interference elimination method based on spread spectrum communication applied to satellite transmission service, which comprises the following steps: S1, performing FFT (Fast Fourier Transform) operation on a digital baseband signal, converting the digital baseband signal into a frequency domain signal, determining a judgment threshold according to the background noise power, and judging a component greater than the threshold as an interference signal; s2, based on a sequential return-to-zero algorithm or a sequential pruning algorithm, frequency points with interference signal components in each frequency domain under the AWGN condition are cut off; s3, using windowed FFT operation, and popularizing the application under the AWGN condition in the S2 to the application under the narrowband interference condition; and S4, reducing the frequency domain signal after the interference signal component frequency points are removed into a time domain signal by adopting IFFT (Inverse Fast Fourier Transform) operation. The method has a good application prospect in the fields of manufacturing of space-based satellite systems and other spacecrafts, manufacturing of satellite antennas and other communication system equipment, satellite transmission services and the like.

The invention provides a vector array sparse Bayesian learning direction of arrival estimation method. The method comprises the following steps: constructing a far-field vector sparse signal model; and establishing a noise covariance model under the vector sound field. And estimating a signal power hyper-parameter through a vector array sparse Bayesian learning process. And through a maximum likelihood estimation technology, noise power hyper-parameter estimation is realized. And finally, carrying out peak searching on the converged signal power hyper-parameter to obtain a direction of arrival estimation result. The method has the advantages that the vector array signal processing performance advantage is obtained, higher signal processing gain is obtained, and meanwhile the method has the capability of restraining the azimuth ambiguity problem; and by using the difference between the noise covariance matrix and the signal covariance matrix under the vector noise, the estimation precision of hyper-parameters such as the signal power and the noise power is remarkably improved. Compared with a traditional vector array DOA estimation method, the vector array DOA estimation method has a lower spectrum background and a sharper spatial spectrum peak, and the resolution and DOA estimation precision are remarkably superior to those of other methods.

A measurement system for determining a noise figure of a device under test is described. The measurement system determines a first total error power based on the output signal by a first noise canceling technique, wherein the first total error power includes systematic errors originating in the device under test and in the measurement system. The measurement system determines a second total error power based on the output signal by a different, second noise canceling technique. The second total error power includes systematic errors originating in the measurement system. The second total error power further includes noise originating in the device under test and in the measurement system outside of the measurement instrument. The measurement system is configured to subtract the first total error power from the second total error power, thereby obtaining an external noise power.

The invention provides a filtering method and device for channel estimation, electronic equipment and a storage medium. The method comprises the following steps: acquiring initial channel estimation of a reference signal, and determining optimal noise power in a current target channel scene based on the initial channel estimation; performing first-stage Wiener filtering on the initial channel estimation to obtain first filtering channel estimation; and performing second-stage Wiener filtering on the first filtering channel estimation based on the optimal noise power to obtain second filtering channel estimation. Therefore, according to the scheme, the optimal noise power in the target channel scene is acquired in advance, so that the second-stage Wiener filtering can be immediately carried out after the first-stage Wiener filtering is completed, the process of carrying out noise estimation on the reference signal after the first-stage filtering can be omitted, the processing waiting time is reduced, and the processing efficiency is improved. And the processing time delay is reduced, so that the two-stage filter circuit can be designed in a tight coupling manner to enhance the stability of the filter performance.

The invention discloses a cable partial discharge signal noise separation mode identification method and system, and particularly relates to the technical field of cable partial discharge detection, in a multi-cable stacking environment, partial discharge signals are synchronously collected through multiple types of sensors such as a high-frequency current sensor, an ultrasonic sensor and an electromagnetic antenna; performing band-pass filtering, wavelet denoising and multi-channel synchronous alignment on the acquired signals to suppress background noise and retain key features of partial discharge pulses; separating the mixed signals by adopting independent component analysis; calculating a decision coefficient based on an inter-channel correlation coefficient, a signal-noise power ratio and an amplitude dynamic range, and judging whether to introduce a denoising method based on deep learning; for the waveform after noise separation, executing an amplitude re-calibration process so as to correct amplitude scaling uncertainty, and extracting multi-dimensional time domain, frequency domain and phase features; and a support vector machine and other machine learning algorithms are combined to realize automatic identification of partial discharge types.

Some embodiments of the present disclosure relate to apparatuses and methods for establishing signal-to-noise ratio (SNR), available signal power level (Es), and man-made noise power level (Noc) values for new radio (NR) performance requirements. These apparatuses and methods may include processing a received signal including the Es and Noc; and determining a baseband SNR attenuation based on the signal power level, the man-made noise power level, and the radio frequency noise power level. These apparatuses and methods may then determine a compensated SNR attenuation as a performance requirement based on the baseband SNR attenuation and the radio frequency noise power level.

The invention discloses a method for adjusting transmitting power in satellite communication, and belongs to the technical field of satellite communication. The method comprises the following steps: firstly, scanning a communication frequency band and an adjacent frequency band by using spectrum monitoring equipment on a satellite, constructing a plurality of background noise power sequences and extracting background noise features; a corresponding sequence is formed according to the bit error rate and the signal-to-noise ratio of the satellite emission signal, and bit error rate features and signal-to-noise ratio features are extracted; acquiring a demand coefficient according to the newest bit error rate and the difference between the signal-to-noise ratio and the target value; and finally, inputting a plurality of groups of background noise features, bit error rate features, signal-to-noise ratio features and demand coefficients as samples into the trained full connection layer-BP neural network to obtain a transmitting power increment, adding the transmitting power increment with the initial transmitting power, and determining the transmitting power of the next signal, thereby effectively improving the transmitting power adjustment precision.

The invention discloses a multi-bandwidth spectrum data signal adaptive extraction method based on a signal-to-noise ratio threshold, and relates to the technical field of spectrum signal extraction. The frequency spectrum data collection covers 30MHz-6GHz, the sampling rate is 20MHz, 16-bit quantization is realized, and the hardware fluctuation is eliminated through the dual-channel design; according to noise floor estimation, 50 frames of no-signal samples are taken, mean value calculation is carried out through a sliding window, then median filtering is carried out, and the noise power and confidence interval of each frequency point are obtained; basic values are set for a signal-to-noise ratio threshold according to frequency bands, dynamic adjustment is performed in combination with real-time noise standard deviation, and compensation is added to a known frequency band; for multi-bandwidth detection, wavelet packet decomposition is adapted to 100kHz-5MHz, candidate signals are marked when energy detection exceeds a threshold, and a range is determined by morphological filtering; extracting parameters such as center frequency, analyzing time-frequency characteristics through short-time Fourier transform, and calculating 4-order cumulants to establish feature vectors; coherent accumulation times are adjusted according to a signal-to-noise ratio, energy is superposed through phase alignment, and a purified signal is output through band-pass filtering. According to the invention, the signal detection precision and adaptability in a complex environment are improved, and misjudgment is reduced.

The invention discloses a high-precision magnetic field data acquisition unit for aeromagnetic measurement and an acquisition method thereof, belongs to the technical field of aeromagnetic measurement, and solves the problems that the acquisition resolution of an aeromagnetic measurement magnetic field is low, the measurement precision is influenced by a power supply and electromagnetic interference, and the data processing and storage reliability is insufficient. According to the invention, a framework of'acquisition module + control module 'is adopted, the acquisition module realizes high-precision sampling through low-noise power supply, differential reference and analog front-end full-link conditioning, the control module completes error compensation and aeromagnetic compensation through a Zynq core, and the 1nT-level magnetic field acquisition precision is achieved by matching an anti-interference design and stable storage and transmission. The 1nT-level magnetic field acquisition precision in the aeromagnetic measurement process is achieved, the signal acquisition precision and stability are remarkably improved, electromagnetic and power interference is effectively inhibited, the reliability of data processing, storage and transmission is guaranteed, and the strict requirements of aeromagnetic measurement for precision and interference resistance are met.

The invention discloses a subarray beam domain high-resolution spatial spectrum estimation method under an under-snapshot condition. The method comprises the following steps: step 1, uniformly dividing N-element towed linear array sonar array element frequency domain data into K subarrays; 2, performing beam forming processing on each piece of sub-array data to obtain a beam domain result of each sub-array; 3, calculating a beam domain steering vector; 4, calculating a beam domain covariance matrix; 5, realizing signal and noise power parameter estimation based on a sparse approximate minimum variance criterion; and 6, carrying out frequency band weighted summation on the estimated signal power to obtain a broadband DOA estimation result. According to the method, sub-array division dimensionality reduction, beam domain coherent processing and sparse parameter iteration estimation are combined for processing, the method has the advantages of low snapshot adaptability and high anti-interference capability, the method can be used for near-field weak signal detection of the towed linear array under multi-target interference, and effectiveness is verified through marine test data.

The embodiment of the invention provides a short-wave full-frequency staring-distributed cooperative frequency, channel and link measurement method. The method is applied to the field of short-wave measurement, and comprises the following steps: performing multi-phase filtering on a received broadband signal to obtain a multi-channel signal; determining signal power and noise power of the multi-channel signal, and determining frequency availability according to the signal power and the noise power; selecting an available frequency according to the frequency availability, measuring through a linear frequency modulation signal transmitted in a channel to obtain a channel characteristic parameter, and determining the channel availability according to the channel characteristic parameter; signals with different waveforms are transmitted in a specified link, link characteristics are obtained through measurement, and link availability is determined according to the link characteristics; the frequency availability, the channel availability and the link availability are subjected to statistical analysis to obtain a statistical analysis result, data support is provided for multi-link cooperative transmission strategy adjustment and link access decision, and the efficiency and reliability of short-wave communication are improved.

The invention provides a signal detection method and device, equipment, a chip and a medium, and the method comprises the steps: obtaining a receiving signal corresponding to a control resource set CORESET to be subjected to blind detection; determining signal power and noise power of a control channel element (CCE) corresponding to the candidate physical downlink control channel (PDCCH) according to the pilot signal and the received signal of the CORESET; according to the signal power and the noise power of the CCE, determining the total signal-to-noise ratio of the candidate PDCCH and the target signal-to-noise ratio of the CCE; and determining whether the candidate PDCCH contains an effective signal according to the total signal-to-noise ratio and the target signal-to-noise ratio. The technical problem of high overhead of signal detection in the prior art is solved.

The invention relates to an LDPC (Low Density Parity Check) quantitative hierarchical decoding working method combining an improved dragonfly algorithm with residual degradation, and belongs to the technical field of wireless communication. The method specifically comprises the steps that firstly, a pilot signal is sent by a signal source, average least square estimation of channel state information is obtained through analysis based on representation of a received signal in a time domain and a frequency domain, noise power is determined, then the pilot signal is introduced into an improved dragonfly algorithm, quantization parameter set training is carried out, and the improved dragonfly algorithm reads a sample signal to obtain the channel state information. And finally, applying the self-adaptive quantization parameter set obtained by training to a residual degradation decoding algorithm, and if a decoding result does not meet a verification equation, carrying out next iteration. The performance of the residual degradation decoding algorithm is superior to that of the DLNMS, hardware resources are saved, the decoding performance of layered quantization is improved, the decoding time is shortened, and therefore the decoding speed is increased.

The invention provides a water quality suspended matter detection system and method based on sensing data, and belongs to the technical field of water quality suspended matter detection. Gain compensation is performed on a mixed optical signal based on backward spontaneous radiation noise power, so that the influence of self gain drift of a sensor and environmental interference on a signal baseline is effectively eliminated; the adaptive variational mode decomposition algorithm decomposes the standardized signal into a plurality of intrinsic mode functions, accurately extracts signals strongly related to the physical characteristics of the target suspended particulate matter, generates a particulate matter characteristic waveform signal with an optimized signal-to-noise ratio through the intrinsic mode functions screened out through weighted stacking, further highlights the time-frequency characteristics of the target signal, and improves the accuracy of the particulate matter characteristic waveform signal. Each independent particulate matter signal event is accurately separated by adopting a dynamic threshold peak value detection algorithm, and the detection accuracy is improved by extracting a multi-dimensional feature vector from each signal event and distinguishing target particulate matters from interferents by utilizing a pre-trained event classifier.

The invention discloses a PDCCH (Physical Downlink Control Channel) blind detection method and device, terminal equipment and a storage medium. The method comprises the following steps: acquiring a broadband signal to interference plus noise ratio and broadband noise power; determining a current blind detection aggregation grade sequence according to the broadband signal to interference plus noise ratio; according to a current blind detection aggregation level sequence, performing blind detection on all candidate sets under each aggregation level in sequence, and determining a physical resource position of a current candidate set; calculating a CCE-level signal to interference plus noise ratio and CCE-level noise power of a control channel unit of the current candidate set; according to the CCE-level signal to interference plus noise ratio and the CCE-level noise power of the current candidate set, and the broadband signal to interference plus noise ratio and the broadband noise power, carrying out early stop judgment; and if early stop is needed, current candidate detection is stopped, and next candidate set detection is started. By means of the scheme, the blind detection quality can be guaranteed, meanwhile, the blind detection time is shortened, and the system power consumption is saved.

The invention provides an 802.11 be multi-user system receiver signal-to-noise ratio estimation method, device and equipment and a medium, and the method does not only depend on a limited number of pilot frequency subcarriers in a frequency resource unit where a target user is located any more, but analyzes and verifies an EHT-SIG field to estimate the signal-to-noise ratio of the target user. And a plurality of frequency resource units whose cyclic redundancy check results are verified to be correct are screened out, and all pilot frequency subcarriers contained in the reliable frequency resource units are combined to be jointly used for estimation. According to the method, a plurality of cyclic redundancy check results are combined to check all reliable pilot frequency subcarriers in a correct frequency resource unit to estimate the signal-to-noise ratio, so that the sample cardinal number of noise power estimation is remarkably increased; the problem of low estimation precision caused by too few pilot frequency subcarriers of a single user due to dynamic allocation in an 802.11 be multi-user system is effectively solved, so that the overall accuracy of signal-to-noise ratio estimation is improved.

The present disclosure provides a constant false alarm rate-based downhole casing nondestructive testing method, device and medium. The method can include: obtaining a detection threshold according to a preset false alarm probability and background noise power of a target pulsed eddy current array detection signal, wherein the false alarm probability refers to the probability that the detection system incorrectly determines the presence of a damaged target when a non-damaged target is present in the downhole casing; screening the target pulsed eddy current array detection signal based on the detection threshold to obtain a downhole casing damage detection result signal; and determining the position of the downhole casing damage according to the downhole casing damage detection result signal. Through this technical solution, the detection threshold can be dynamically adjusted, and the position of the downhole casing damage can be accurately located, thereby improving the efficiency and accuracy of downhole casing damage detection.

A user equipment (UE) is configured to report channel state information (CSI) to a base station of a network. The UE receives configuration information from the base station including one or more interference measurement resources (IMRs) to be measured by the UE, determines noise power for each of the IMRs, transmits a reference channel state information (CSI) report to the base station, measures a CSI reference signal (CSI RS) transmitted by the base station to determine interference and noise power for each of the one or more IMRs, and transmits a new CSI report to the base station including either i) only interference and noise power fluctuation feedback or ii) multiple signal-to-interference-plus-noise ratios (SINRs) or SINR statistics.

The application relates to a real-valued super-resolution direction estimation method of a high-order acoustic field sensor array, which uses a received signal covariance matrix to approximately calculate an estimated value of noise power, avoids the iterative operation process of noise power in the prior art, improves the calculation efficiency, and reduces the floating-point operation amount. By constructing an augmented matrix, the array receiving data matrix and the array manifold matrix with a multi-dimensional structure of an element are made into Hermitian matrices, so that the unitary transformation processing of the related parameters of the high-order acoustic field sensor array is realized. On the basis of obtaining the array receiving data matrix and the array manifold matrix in the real number domain, the array receiving data matrix and the array manifold matrix are applied to a sparse approximate minimum variance method with a variable exponential factor, and the completely real-valued sparse approximate minimum variance direction estimation with a variable exponential factor is realized.

The present application relates to the technical field of array signal processing and wireless communication, and particularly relates to a beacon source assisted self-calibration and robust beamforming method, comprising: collecting array snapshot data and constructing sample covariance; extracting spatial features based on coarse direction prior of auxiliary signal source and performing reliability determination; estimating geometric drift parameters through per-element phase ratio estimation; constructing parameterized covariance model based on calibrated array manifold and estimating noise power; estimating power coefficients of each signal source by using non-negative constraint fitting estimation; reconstructing INCM and optionally diagonally loading to enhance reversibility; calculating MVDR weight vector based on reconstructed INCM and outputting beamforming result; when reliability determination fails, falling back to nominal geometry or preset geometry to avoid false calibration. The present application has the advantages of geometric self-calibration, low snapshot robustness, false calibration prevention and wide application range.

The invention discloses a millimeter wave detection anti-noise performance improvement method and a millimeter wave detection anti-noise performance improvement system, relates to the technical field of anti-noise performance improvement, and is used for solving the problem of defect discrimination sensitivity and positioning precision reduction caused by insufficient identification accuracy of sound wave or radar detection in a high-humidity and high-noise tunnel environment. Target echo power is calculated by transmitting millimeter wave signals and receiving tunnel wall surface echoes, noise is collected and noise power is extracted, a gain adjustment coefficient is obtained based on the ratio of the two echoes, target signals are amplified, and a judgment threshold value is generated by combining wall surface material reflection characteristics so as to identify structural defects and generate abnormal information. The method comprises the following steps: adjusting the bandwidth of a receiving filter to obtain an optimized echo signal, analyzing the type, position and severity of a defect, extracting a multi-path echo delay difference to realize accurate positioning, and finally judging whether to generate early warning information or not by combining the delay difference and abnormal information, thereby improving the detection precision and response speed of the system under noise interference.

A method for monitoring generalized optical signal-to-noise ratio (gOSNR) is provided, which is applied to monitoring of an optical signal received by a coherent receiver through a fiber link. The method includes: obtaining a first received waveform; obtaining a signal part of the first received waveform; obtaining a noise part of the first received waveform according to the signal part and the first received waveform; obtaining a first correlation between the noise part and a first template at a predetermined location on the fiber link, the first correlation indicating a signal power at the predetermined location; obtaining a second correlation between the noise part and a second template at the predetermined location on the fiber link, the second correlation indicating a signal power and noise power at the predetermined location; and obtaining gOSNR at the predetermined location according to the first correlation and the second correlation.

The application discloses a speech enhancement method, device and electronic equipment, the method comprises the following steps: acquiring speech recognition confidence and a to-be-enhanced speech signal, and converting the to-be-enhanced speech signal into a frequency domain signal, wherein the speech recognition confidence is a confidence degree representing that the speech signal contains a user speech instruction; calculating a noise power estimation value based on the speech recognition confidence and the frequency domain signal; and performing adaptive beamforming by using the frequency domain signal and the noise power estimation value to obtain an enhanced speech signal. According to the technical scheme provided by the application, the speech recognition confidence of the speech signal is introduced to adjust the noise power estimation value, so that a more accurate noise power estimation value is obtained, and then the adaptive beamforming algorithm is executed based on the noise power estimation value, so that the speech enhancement effect can be improved in a low signal-to-noise ratio scene, and a more reliable enhanced speech signal is obtained.

The application belongs to the field of GPS positioning, and relates to a dynamic GPS signal interference influence evaluation method and system, which comprises the following steps: calculating the instantaneous position vectors and velocity vectors of visible satellites, a receiver and an interference source in the Earth-Centered Earth-Fixed coordinate system; obtaining the directional gain of a receiving antenna to multiple visible satellite signals and multiple interference signals respectively; calculating the noise power spectral density, the power of multiple visible satellite signals and the power of multiple interference signals arriving at the radio frequency front end of the receiver; modeling the equivalent carrier-to-noise ratio to obtain the equivalent carrier-to-noise ratio of multiple visible satellites; simulating the influence of the visible satellites on the code tracking loop of the receiver to obtain the pseudorange measurement error of multiple visible satellites; and performing positioning solution through a weighted matrix least square method to obtain the positioning accuracy, so that the interference effect can be accurately, real-timely and quantitatively evaluated.

The invention provides an OFDM (Orthogonal Frequency Division Multiplexing) system signal demodulation method and system based on dynamic noise estimation, and belongs to the technical field of power line communication. The method comprises the following steps: acquiring a receiving frequency domain signal of an OFDM symbol; calculating a noise estimation value according to the received frequency domain signal; according to the noise estimation value, calculating a mean value estimation value of the noise variance or a median estimation value of the noise square, and according to the mean value estimation value of the noise variance or the median estimation value of the noise square, calculating a noise power estimation value; calculating a dynamic weight according to the noise power estimation value; obtaining a balanced receiving frequency domain signal according to the receiving frequency domain signal and the dynamic weight; and performing demodulation judgment on the balanced receiving frequency domain signal to obtain a signal demodulation result. The method can adapt to a time-varying noise environment in power line communication, so that the signal receiving performance is improved.

The invention provides a medium-voltage line topology identification method based on a KNN classifier and a related device, and the method comprises the steps: collecting the signal power and noise power of topology identification equipment under different frequencies, and calculating the useful signal power of a self-transmitting and self-receiving micro-current and a self-transmitting and self-receiving micro-current; thirdly, in combination with an actual field shunting condition, taking frequency information, two types of useful signal power and shunting data as input, and training a KNN model; and finally, inputting frequency information of actual operation and two types of useful signal power into the model, adaptively outputting shunt judgment, and fusing non-shunt data to obtain actual topological information. According to the invention, through data training learning, the line shunting phenomenon is effectively identified, and the topology identification accuracy is improved.

The application relates to a channel estimation method, device, electronic equipment, storage medium and program product, and relates to the technical field of communication. The channel estimation method comprises the following steps: determining a pilot signal matrix according to the number of transmitting antennas and the pilot length corresponding to the communication signal of a target channel; constructing a to-be-processed matrix of the target channel according to the pilot signal matrix, the noise power of the communication signal and the number of receiving antennas; determining time domain weight and frequency domain weight based on a correlation influence parameter and a weight decision model; generating an iteration initial value according to the time domain weight, a first reference matrix corresponding to a second time slot and a first subcarrier, the frequency domain weight and a second reference matrix corresponding to a first time slot and a second subcarrier; performing iteration operation on the to-be-processed matrix according to the iteration initial value and a preset inverse iteration model; and obtaining the inverse matrix of the to-be-processed matrix to determine the channel matrix of the target channel when the preset iteration termination condition is met. The method can improve the communication performance.